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Summary Of Kavita Ganesan S The Business Case For Ai


Summary Of Kavita Ganesan S The Business Case For Ai
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Summary Of Kavita Ganesan S The Business Case For Ai


Summary Of Kavita Ganesan S The Business Case For Ai
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Author : Milkyway Media
language : en
Publisher: Milkyway Media
Release Date : 2024-01-22

Summary Of Kavita Ganesan S The Business Case For Ai written by Milkyway Media and has been published by Milkyway Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-22 with Computers categories.


Get the Summary of Kavita Ganesan's The Business Case for AI in 20 minutes. Please note: This is a summary & not the original book. "The Business Case for AI" by Kavita Ganesan explores the transformative impact of Artificial Intelligence (AI) on business operations. It details how AI automates tasks, reduces human error, and provides strategic insights, with examples like Visa's fraud detection and AI's role in healthcare diagnostics. The book emphasizes that AI augments human capabilities, focusing on artificial narrow intelligence (ANI) for specialized tasks...



The Business Case For Ai


The Business Case For Ai
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Author : Kavita Ganesan
language : en
Publisher: Opinosis Analytics Publishing
Release Date : 2022-04-05

The Business Case For Ai written by Kavita Ganesan and has been published by Opinosis Analytics Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-05 with categories.


AI is much more than a sexy marketing gimmick. At its core, it's a powerful business tool that can make operations more efficient, employees more productive, and customers delighted. Unfortunately, leaders who want to take advantage of AI often don't know where to start. The process can feel overwhelming-from choosing where to apply AI to preparing every tier of the organization for the transition. In this practical guide for business leaders, Kavita Ganesan takes the mystery out of implementing AI, showing you how to launch AI initiatives that get results. With real-world AI examples to spark your own ideas, you'll learn how to identify high-impact AI opportunities, prepare for AI transitions, and measure your AI performance. Simple and compelling, The Business Case for AI gives leaders the information they need without the technical jargon. Whether you want to jumpstart your AI strategy, manage your AI initiatives for better outcomes, or simply find inspiration for your own AI applications, The Business Case for AI is your blueprint for AI success.



The Business Case For Ai


The Business Case For Ai
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Author : Kavita Ganesan
language : en
Publisher: Opinosis Analytics
Release Date : 2022-04-05

The Business Case For Ai written by Kavita Ganesan and has been published by Opinosis Analytics this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-05 with Business & Economics categories.


AI is much more than a sexy marketing gimmick. At its core, it’s a powerful business tool that can make operations more efficient, employees more productive, and customers delighted. Unfortunately, leaders who want to take advantage of AI often don’t know where to start. The process can feel overwhelming—from choosing where to apply AI to preparing every tier of the organization for the transition. In this practical guide for business leaders, Kavita Ganesan takes the mystery out of implementing AI, showing you how to launch AI initiatives that get results. With real-world AI examples to spark your own ideas, you’ll learn how to identify high-impact AI opportunities, prepare for AI transitions, and measure your AI performance. Simple and compelling, The Business Case for AI gives leaders the information they need without the technical jargon. Whether you want to jumpstart your AI strategy, manage your AI initiatives for better outcomes, or simply find inspiration for your own AI applications, The Business Case for AI is your blueprint for AI success. Topics covered include: -Real-World AI Use Cases -What's AI in Business -The B-CIDS: The 5 pillars of AI preparation (or readiness) -The Jumpstart AI Approach -The HI-AI Discovery Framework -Measuring AI Success And more throughout the book…



Generative Adversarial Networks For Image To Image Translation


Generative Adversarial Networks For Image To Image Translation
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Author : Arun Solanki
language : en
Publisher: Academic Press
Release Date : 2021-06-22

Generative Adversarial Networks For Image To Image Translation written by Arun Solanki and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-22 with Science categories.


Generative Adversarial Networks (GAN) have started a revolution in Deep Learning, and today GAN is one of the most researched topics in Artificial Intelligence. Generative Adversarial Networks for Image-to-Image Translation provides a comprehensive overview of the GAN (Generative Adversarial Network) concept starting from the original GAN network to various GAN-based systems such as Deep Convolutional GANs (DCGANs), Conditional GANs (cGANs), StackGAN, Wasserstein GANs (WGAN), cyclical GANs, and many more. The book also provides readers with detailed real-world applications and common projects built using the GAN system with respective Python code. A typical GAN system consists of two neural networks, i.e., generator and discriminator. Both of these networks contest with each other, similar to game theory. The generator is responsible for generating quality images that should resemble ground truth, and the discriminator is accountable for identifying whether the generated image is a real image or a fake image generated by the generator. Being one of the unsupervised learning-based architectures, GAN is a preferred method in cases where labeled data is not available. GAN can generate high-quality images, images of human faces developed from several sketches, convert images from one domain to another, enhance images, combine an image with the style of another image, change the appearance of a human face image to show the effects in the progression of aging, generate images from text, and many more applications. GAN is helpful in generating output very close to the output generated by humans in a fraction of second, and it can efficiently produce high-quality music, speech, and images. Introduces the concept of Generative Adversarial Networks (GAN), including the basics of Generative Modelling, Deep Learning, Autoencoders, and advanced topics in GAN Demonstrates GANs for a wide variety of applications, including image generation, Big Data and data analytics, cloud computing, digital transformation, E-Commerce, and Artistic Neural Networks Includes a wide variety of biomedical and scientific applications, including unsupervised learning, natural language processing, pattern recognition, image and video processing, and disease diagnosis Provides a robust set of methods that will help readers to appropriately and judiciously use the suitable GANs for their applications



The Ai Powered Enterprise


The Ai Powered Enterprise
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Author : Seth Earley
language : en
Publisher: LifeTree Media
Release Date : 2020-04-28

The Ai Powered Enterprise written by Seth Earley and has been published by LifeTree Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-28 with Business & Economics categories.


Learn how to develop and employ an ontology, the secret weapon for successfully using artificial intelligence to create a powerful competitive advantage in your business. The AI-Powered Enterprise examines two fundamental questions: First, how will the future be different as a result of artificial intelligence? And second, what must companies do to stake their claim on that future? When the Web came along in the mid-90s, it transformed the behavior of customers and remade whole industries. Now, as part of its promise to bring revolutionary change in untold ways to human activity, artificial intelligence—AI—is about to create another complete transformation in how companies create and deliver value to customers. But despite the billions spent so far on bots and other tools, AI continues to stumble. Why can't it magically use all the data organizations generate to make them run faster and better? Because something is missing. AI works only when it understands the soul of the business. An ontology is a holistic digital model of every piece of information that matters to the business, from processes to products to people, and it's what makes the difference between the promise of AI and delivering on that promise. Business leaders who want to catch the AI wave—rather than be crushed by it—need to read The AI-Powered Enterprise. The book is the first to combine a sophisticated explanation of how AI works with a practical approach to applying AI to the problems of business, from customer experience to business operations to product development.



Artificial Intelligence In Practice


Artificial Intelligence In Practice
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Author : Bernard Marr
language : en
Publisher: John Wiley & Sons
Release Date : 2019-04-15

Artificial Intelligence In Practice written by Bernard Marr and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-15 with Business & Economics categories.


Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce.



Intelligent Automation


Intelligent Automation
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Author : PASCAL. BARKIN BORNET (IAN. WIRTZ, JOCHEN.)
language : en
Publisher:
Release Date : 2020

Intelligent Automation written by PASCAL. BARKIN BORNET (IAN. WIRTZ, JOCHEN.) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Electronic books categories.




Artificial Intelligence For Business Leaders


Artificial Intelligence For Business Leaders
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Author : Ajit Jha
language : en
Publisher: Independently Published
Release Date : 2020-07-23

Artificial Intelligence For Business Leaders written by Ajit Jha and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-23 with categories.


◆◆ "Embrace artificial intelligence or be replaced by it." ◆◆ "AI is a new electricity." Andrew Ng ✓Have you ever thought that if AI is the new electricity, why does it not quickly inspire Managers/Leaders/C-Suites? ✓If business leaders do not act, they must be prepared to lag behind competitors who adopt new technologies. ✓Managers/Leaders/C-Suites and others who are willing to feel the spark of AI, should learn and understand AI immediately to know what AI can do and what it cannot. ✓Did you know that AI is changing our world faster than we think? Artificial intelligence will affect all areas of life in ways we cannot even predict, whether we like it or not. According to research done by PricewaterhouseCoopers (PwC), by 2030, artificial intelligence can contribute up to US$15.7 trillion to the global economy, so the opportunities for implementing and learning AI are huge. ⚠ Companies that do not use AI will soon become obsolete. From making faster and better decisions to automating rote memorization to enabling robots to respond to emotions, artificial intelligence and machine learning have been reshaping business and society. ⚠ Not investing in the organizational and technical requirements of adopting AI may mean that they are far behind and unable to compete in the future. ✓ Business is changing. Will you adapt or fall behind? Accelerate and deepen your understanding of the themes that shape the company's future. ✓ This book is suitable for business executives, business managers, business leaders, senior managers, technical leaders, students, and many people who want to understand artificial intelligence. ✓ It will take you to learn the concepts of machine learning, artificial intelligence and deep learning, more and how to use them to influence your business. ✓✓ Even if you do not have technical knowledge, you will understand AI, ML and its implementation. ◆◆ Key features ◆◆ nbsp; ★ A must book for the business leader to understand AI and its application ★ Understand strategy behind AI implementation ★ Zero coding with simple explanation ★ A straightforward explanation for important algorithms like TensorFlow, NLP, K-Means, Support Vector Machine, Supervised Learning, Unsupervised Learning, Ensemble Techniques, Regression, Clustering, and many more ★★ Grab your copy of this book to build artificial intelligence for business and stand to the best of times!



Succeeding With Ai


Succeeding With Ai
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Author : Veljko Krunic
language : en
Publisher: Manning Publications
Release Date : 2020-03-31

Succeeding With Ai written by Veljko Krunic and has been published by Manning Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-31 with Business & Economics categories.


Summary Companies small and large are initiating AI projects, investing vast sums of money on software, developers, and data scientists. Too often, these AI projects focus on technology at the expense of actionable or tangible business results, resulting in scattershot results and wasted investment. Succeeding with AI sets out a blueprint for AI projects to ensure they are predictable, successful, and profitable. It’s filled with practical techniques for running data science programs that ensure they’re cost effective and focused on the right business goals. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Succeeding with AI requires talent, tools, and money. So why do many well-funded, state-of-the-art projects fail to deliver meaningful business value? Because talent, tools, and money aren’t enough: You also need to know how to ask the right questions. In this unique book, AI consultant Veljko Krunic reveals a tested process to start AI projects right, so you’ll get the results you want. About the book Succeeding with AI sets out a framework for planning and running cost-effective, reliable AI projects that produce real business results. This practical guide reveals secrets forged during the author’s experience with dozens of startups, established businesses, and Fortune 500 giants that will help you establish meaningful, achievable goals. In it you’ll master a repeatable process to maximize the return on data-scientist hours and learn to implement effectiveness metrics for keeping projects on track and resistant to calcification. What's inside Where to invest for maximum payoff How AI projects are different from other software projects Catching early warnings in time to correct course Exercises and examples based on real-world business dilemmas About the reader For project and business leadership, result-focused data scientists, and engineering teams. No AI knowledge required. About the author Veljko Krunic is a data science consultant, has a computer science PhD, and is a certified Six Sigma Master Black Belt. Table of Contents: 1. Introduction 2. How to use AI in your business 3. Choosing your first AI project 4. Linking business and technology 5. What is an ML pipeline, and how does it affect an AI project? 6. Analyzing an ML pipeline 7. Guiding an AI project to success 8. AI trends that may affect you



Deep Learning Patterns And Practices


Deep Learning Patterns And Practices
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Author : Andrew Ferlitsch
language : en
Publisher: Simon and Schuster
Release Date : 2021-10-12

Deep Learning Patterns And Practices written by Andrew Ferlitsch and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-12 with Computers categories.


Discover best practices, reproducible architectures, and design patterns to help guide deep learning models from the lab into production. In Deep Learning Patterns and Practices you will learn: Internal functioning of modern convolutional neural networks Procedural reuse design pattern for CNN architectures Models for mobile and IoT devices Assembling large-scale model deployments Optimizing hyperparameter tuning Migrating a model to a production environment The big challenge of deep learning lies in taking cutting-edge technologies from R&D labs through to production. Deep Learning Patterns and Practices is here to help. This unique guide lays out the latest deep learning insights from author Andrew Ferlitsch’s work with Google Cloud AI. In it, you'll find deep learning models presented in a unique new way: as extendable design patterns you can easily plug-and-play into your software projects. Each valuable technique is presented in a way that's easy to understand and filled with accessible diagrams and code samples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Discover best practices, design patterns, and reproducible architectures that will guide your deep learning projects from the lab into production. This awesome book collects and illuminates the most relevant insights from a decade of real world deep learning experience. You’ll build your skills and confidence with each interesting example. About the book Deep Learning Patterns and Practices is a deep dive into building successful deep learning applications. You’ll save hours of trial-and-error by applying proven patterns and practices to your own projects. Tested code samples, real-world examples, and a brilliant narrative style make even complex concepts simple and engaging. Along the way, you’ll get tips for deploying, testing, and maintaining your projects. What's inside Modern convolutional neural networks Design pattern for CNN architectures Models for mobile and IoT devices Large-scale model deployments Examples for computer vision About the reader For machine learning engineers familiar with Python and deep learning. About the author Andrew Ferlitsch is an expert on computer vision, deep learning, and operationalizing ML in production at Google Cloud AI Developer Relations. Table of Contents PART 1 DEEP LEARNING FUNDAMENTALS 1 Designing modern machine learning 2 Deep neural networks 3 Convolutional and residual neural networks 4 Training fundamentals PART 2 BASIC DESIGN PATTERN 5 Procedural design pattern 6 Wide convolutional neural networks 7 Alternative connectivity patterns 8 Mobile convolutional neural networks 9 Autoencoders PART 3 WORKING WITH PIPELINES 10 Hyperparameter tuning 11 Transfer learning 12 Data distributions 13 Data pipeline 14 Training and deployment pipeline